Question 277 of 499
Operationalizing machine learning modelsmediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is that an alert will be sent to admin@example.com. This is correct because Vertex AI Model Monitoring triggers alerts based on per-feature skew thresholds; the configuration shows a threshold of 0.2 for the feature 'age', and a measured skew of 0.4 exceeds that value, activating the specified email notification action. On the Google Professional Data Engineer exam, this scenario tests your understanding that monitoring is feature-specific—a common trap is assuming alerts are triggered by aggregate or default thresholds rather than the exact value set for each feature. The key distinction is that the alert action (email, Pub/Sub, etc.) is tied directly to the feature’s threshold breach, not to any other feature’s status. Memory tip: think "feature-first, threshold-triggered"—each feature’s skew alert fires independently when its own numeric limit is crossed.

PDE Operationalizing machine learning models Practice Question

This PDE practice question tests your understanding of operationalizing machine learning models. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

Exhibit

Refer to the exhibit.

```
$ gcloud ai endpoints describe my-endpoint
...
modelDeploymentMonitors:
- model: projects/my-project/models/my-model
  objectiveConfig:
    objectiveType: skew
    skewConfig:
      featureSkewThresholds:
        age: 0.3
        income: 0.2
  alertConfig:
    enableAlerting: true
    alertEmailAddresses:
    - admin@example.com
```

You configured a model deployment monitor on your Vertex AI endpoint as shown. What will happen when the feature 'age' has a skew of 0.4?

Question 1mediummultiple choice
Full question →

Exhibit

Refer to the exhibit.

```
$ gcloud ai endpoints describe my-endpoint
...
modelDeploymentMonitors:
- model: projects/my-project/models/my-model
  objectiveConfig:
    objectiveType: skew
    skewConfig:
      featureSkewThresholds:
        age: 0.3
        income: 0.2
  alertConfig:
    enableAlerting: true
    alertEmailAddresses:
    - admin@example.com
```

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

An alert will be sent to admin@example.com

Option A is correct because the monitoring configuration shows an alert threshold of 0.2 for the feature 'age', and a skew of 0.4 exceeds that threshold. Vertex AI Model Monitoring will trigger the configured alert action, which in this case is sending an email to admin@example.com. The alert is based on the specific feature's threshold, not on any other feature's threshold.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • An alert will be sent to admin@example.com

    Why this is correct

    Skew 0.4 exceeds threshold 0.3 for age.

    Related concept

    Read the scenario before looking for a memorised answer.

  • The endpoint will automatically roll back to a previous model version

    Why it's wrong here

    The monitor only sends alerts, does not roll back.

  • No alert will be sent because the skew threshold is 0.2 for income

    Why it's wrong here

    The threshold for age is 0.3.

  • An alert will be sent only if both features exceed their thresholds

    Why it's wrong here

    Each feature is monitored independently.

Common exam traps

Common exam trap: answer the scenario, not the keyword

Google Cloud often tests the misconception that alerts require multiple features to exceed thresholds or that the system can automatically roll back models, when in reality each feature is evaluated independently and only notifications are sent.

Detailed technical explanation

How to think about this question

Vertex AI Model Monitoring uses statistical methods like Jensen-Shannon divergence or L-infinity distance to compute feature skew between training and serving distributions. The threshold is configured per feature, and when the skew exceeds the threshold, the monitoring service logs an anomaly and executes the configured notification action (e.g., email, Pub/Sub). In production, this helps detect data drift early, but note that the alert is based on the feature's own threshold, not a combined condition.

KKey Concepts to Remember

  • Read the scenario before looking for a memorised answer.
  • Find the constraint that changes the correct option.
  • Eliminate answers that are true in general but not in this case.

TExam Day Tips

  • Watch for words such as best, first, most likely and least administrative effort.
  • Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this PDE question test?

Operationalizing machine learning models — This question tests Operationalizing machine learning models — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: An alert will be sent to admin@example.com — Option A is correct because the monitoring configuration shows an alert threshold of 0.2 for the feature 'age', and a skew of 0.4 exceeds that threshold. Vertex AI Model Monitoring will trigger the configured alert action, which in this case is sending an email to admin@example.com. The alert is based on the specific feature's threshold, not on any other feature's threshold.

What should I do if I get this PDE question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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Last reviewed: Jun 30, 2026

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